Triple
T15898948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bautzen district |
E385533
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object |
Ohorn
Ohorn is a small municipality in the Free State of Saxony in eastern Germany, known for its rural setting within the Upper Lusatia region.
|
E1183124
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ohorn | Statement: [Bautzen district, containsTown, Ohorn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ohorn Context triple: [Bautzen district, containsTown, Ohorn]
-
A.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
-
B.
Fellhorn
Fellhorn is a prominent mountain in the Allgäu Alps on the German-Austrian border, popular for hiking and skiing near the town of Oberstdorf.
-
C.
Hösthorn
Hösthorn is a poetry collection by Swedish Nobel laureate Erik Axel Karlfeldt, known for its evocative depictions of nature and rural life.
-
D.
Berghaupten
Berghaupten is a small municipality in the Ortenau district of Baden-Württemberg in southwestern Germany, known for its scenic location in the Black Forest region.
-
E.
Stecknadelhorn
Stecknadelhorn is a high alpine peak in the Pennine Alps of Switzerland, known as one of the prominent summits of the Mischabel range.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ohorn Triple: [Bautzen district, containsTown, Ohorn]
Generated description
Ohorn is a small municipality in the Free State of Saxony in eastern Germany, known for its rural setting within the Upper Lusatia region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ohorn Target entity description: Ohorn is a small municipality in the Free State of Saxony in eastern Germany, known for its rural setting within the Upper Lusatia region.
-
A.
Hoche
Hoche is a Paris Métro station located in the northeastern suburb of Pantin, serving as a stop on the city’s Line 5.
-
B.
Fellhorn
Fellhorn is a prominent mountain in the Allgäu Alps on the German-Austrian border, popular for hiking and skiing near the town of Oberstdorf.
-
C.
Hösthorn
Hösthorn is a poetry collection by Swedish Nobel laureate Erik Axel Karlfeldt, known for its evocative depictions of nature and rural life.
-
D.
Berghaupten
Berghaupten is a small municipality in the Ortenau district of Baden-Württemberg in southwestern Germany, known for its scenic location in the Black Forest region.
-
E.
Stecknadelhorn
Stecknadelhorn is a high alpine peak in the Pennine Alps of Switzerland, known as one of the prominent summits of the Mischabel range.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d86da5b800819083a31be937d738b0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1563bd0688190b6f7a695be0a4625 |
completed | April 16, 2026, 9:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb04d4d1c819091d9b3357ca0deca |
completed | May 9, 2026, 10:08 p.m. |
| NEDg | Description generation | batch_69ffb190ae4881909ac299dfa6e7d9b6 |
completed | May 9, 2026, 10:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffb25747148190bc96cf19acf85e29 |
completed | May 9, 2026, 10:16 p.m. |
Created at: April 10, 2026, 4:51 a.m.